How hyperspectral imaging could transform remote sensing In the ever-expanding toolbox of environmental monitoring, hyperspectral imaging (also known as imaging spectroscopy) is emerging as a ...

A team of CU Boulder researchers has introduced a quantum sensing technique that could lead to improvements in how we monitor infrastructure, detect changes in the environment and conduct geophysical ...

Photon Lines’ partner Resonon has been designing and building hyperspectral imaging systems for over 20 years. Their hyperspectral imagers are used around the world in factories, laboratories, ...

This paper addresses the problem of the classification of hyperspectral remote sensing images by support vector machines (SVMs). First, we propose a theoretical discussion and experimental analysis ...

New technology could remotely identify various types of plastics, offering a valuable tool for future monitoring and analysis of oceanic plastic pollution. A new hyperspectral Raman imaging lidar ...

The research introduces a groundbreaking hyperspectral remote sensing method that delivers highly accurate, hour-hectometer-level insights into the horizontal distribution of atmospheric trace gases.

Melgani, F., & Bruzzone, L. (2004). Classification of Hyperspectral Remote Sensing Images with Support Vector Machines. IEEE Transactions on Geoscience and Remote Sensing, 42, 1778-1790.

In both 2021 and 2022, she was included on Clarivate’s list of highly cited researchers. Du’s research focuses on digital image processing and machine learning, and their applications to ...

Although hyperspectral remote sensing technology is one of the irreplaceable technologies for water quality monitoring and has become the scientific community’s consensus, there is no mature theory ...